The Global Positioning System (GPS) and its counterparts in the Global Navigation Satellite System (GNSS) have become thoroughly pervasive in all parts of human society. GPS and GNSS receivers are increasingly being integrated into devices, tools, and vehicles such as agricultural vehicles, construction equipment, and even in autonomously operated vehicles. In order to provide position measurements with a necessary degree of precision, GNSS receivers may be configured to utilize corrections from various sources. Examples of these correction systems include, for example, the Wide Area Augmentation System (WAAS), the Satellite-Based Augmentation System (SBAS), the Real-time Kinematic (RTK) technique, the Precise Point Positioning (PPP) technique, the European Geostationary Navigation Overlay Service (EGNOS), and the like. Using correction data from these sources, a GNSS receiver can account for error sources such as atmospheric delay of GNSS signals, clock errors, and ephemeris errors to derive a more precise position fix.
When a GNSS receiver (or rover) uses correction data from a single reference station (e.g., differential GPS (DGPS) or RTK), there are small bias errors in the corrections for each satellite that are subject to both temporal and spatial decorrelation. With temporal decorrelation, the correction data degrades as time increases since the reference measurements were taken. With spatial decorrelation, the correction data degrades as distance increases between the rover and the site where the reference measurements were taken.
These correction bias errors also exist in systems that use networked reference stations such as SBAS or PPP. Because there is no reference station at the exact rover site, there will be small correction bias errors. These errors are influenced most heavily by atmospheric conditions—ionospheric model error and tropospheric model error. These correction bias errors will be similar for all rovers within a few kilometers of each other, and will change slowly over time, on the order of minutes, as atmospheric conditions change.
By observing the corrections over a large number of measurements, the rover can estimate the correction bias errors. This process, called convergence, can substantially reduce the magnitude of measurement error. A detailed discussion of typical convergence techniques is found in “IMPROVED CONVERGENCE FOR GNSS PRECISE POINT POSITIONING”, by S. Banville, Ph.D. dissertation, Department of Geodesy and Geomatics Engineering, Technical Report No. 294, University of New Brunswick, Fredericton, New Brunswick, Canada, which is incorporated herein by reference. If enough measurements are taken, and the network model is of sufficiently high fidelity, it may be possible for the bias error estimates to converge to centimeter level accuracy, in which case it may be possible to resolve carrier phase ambiguities to provide a position fix with centimeter level accuracy. This occurs more quickly on a multi-frequency band rover where the ionospheric model error is not as onerous as on a single frequency band rover. However, even without full integer ambiguity resolution, a single frequency band rover will benefit from reduced correction bias errors, and can often attain positioning to sub-meter accuracy after sufficient convergence. Thus, systems and methods for reducing convergence times are desired.